Immigration and the Welfare State Revisited: Fiscal Transfers to Immigrants in Canada in 2014
Bibliographic record
Abstract
This paper provides an updated estimate for 2010 for the net fiscal transfer to the recent immigrants who came to Canada between 1985 and 2009. At $5,329 per capita per year, it is significantly lower than the over $6,000 per capita of our earlier estimates. This reflects the Conservative Federal Government’s ambitious efforts to reform immigration policy since taking office in 2006 to better select immigrants who are more prepared to succeed in Canada’s labour market and to refocus immigration policy more on economic class immigrants. This included the elimination of a backlog of around a million immigrants selected under an old dysfunctional system who were judged to be likely to encounter labour-market difficulties and the introduction of the Canada Experience Class. Nevertheless, it should be of concern that in spite of the improvement in the net fiscal cost of recent immigration the overall fiscal cost of fiscal transfers to recent immigrants has continued to grow to $20 to 28 billion as of 2010, up from our earlier estimate of $16 to 24 billion in 2005. \n \nThe fiscal cost of immigration will probably continue to grow in the future as high levels of immigrants are admitted unless the new Express Entry Program for economic class immigrants is more successful at eliminating the income gap between new immigrants and other Canadians than the measures introduced so far and the mix of immigrants is shifted towards more economic class. At an estimated per-capita net fiscal cost of $5,329, the fiscal cost of immigration can be estimated to have risen to the $27 to $35 billion range in 2014. And the 260,000 to 285,000 planned immigrant admissions recently announced by the Immigration Minister for 2015 should add another $1.4 billion to $1.5 billion to the cost with a similar increment coming every year thereafter as long as the high targeted level of immigration is maintained and achieved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".